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�{�{CT�(�CT�(�(�Gx�I{�����A*�?���z$&�H"/T�T0�T�HB�Y�&�YD�I�I�Y��K0���(�����iTiT�'�����T�������������������������������������������������������������������������Y����������	�:!Nutrient - characteristics, stoichiometry and response stimulus of phytoplankton biomass along the southwest coastal waters of India.
Udayakumar P*a, Chandran  Ab, Jean Jose J a,Shibu R, Rajesh B R a, Anoop Krishnan K a

aChemistry and Marine Biology Laboratory
Chemical Sciences Division
Centre for Earth Science Studies
Thiruvananthapuram-31 Kerala, India
Phone: +91 471 2511698, 99
Fax: 0471-2442280

bUniversity College of Applied Life Sciences
Mahatma Gandhi University Regional Centre
Pathanamthitta-45, Kerala, India


*Corresponding author: HYPERLINK "mailto:udayannair@yahoo.com"udayannair@yahoo.com
























Abstract

The study was aimed at how anthropogenic influences have shaped the nutrient dynamics and phytoplankton biomass in the coastal waters of southwest India. Coastal surface water samples were collected seasonally, from five transects in the southwest coast of India during the year 2008. The samples were analyzed for physical, chemical and biological parameters. Significant seasonal and spatial variation was observed in the hydrographic characteristics. Among the nutrients; dissolved Inorganic phosphate concentration was higher than dissolved inorganic nitrogen forms leading to N: P ratios of an average of less than 10, while Si: N ratios were greater than unity indicating that Si(OH)4 is not a limiting nutrient in the surface coastal water. A comparison of ambient nutrient ratios with the Redfield ratio (N: P: Si = 16:1:16) showed �potential stoichiometric N limitation� in the factors that regulate phytoplankton biomass. Most plankton variability along the coast appears to be driven by species of diatoms; Si supply being a driving force. The effect of external nutrient inputs has made the coastal waters biologically productive in terms of Chlorophyll a pigment concentration.  Principal component analyses applied to the dataset, revealed 75% variations in the coastal system produced by riverine, phosphorus, upwelling and aeration factors. 



Keywords: Nutrients; Monitoring; Anthropogenic inflow; Diatoms; Primary production; Southwest  
coastal water; Multivariate analysis














Introduction

Over the last several decades coastal regions throughout the world have experienced increased incidence of harmful or toxic algal blooms. These blooms occur as a result of key nutrients such as nitrogen (N) and phosphorus (P), because the supply rates of these nutrients most often control or �limit� aquatic plant primary production and biomass formation [1]. The direct influences of human population growth, urbanization, agricultural and industrial expansion have accelerated nutrient over-enrichment in receiving waters [2]. Increased nutrient supply in coastal waters can cause several environmental modifications, such as increase in productivity and fishery potential [3]. However, continual nutrient enrichment promotes accelerated production of plant-based organic matter (i.e., eutrophication) to the extent that excessive production; including noxious algal blooms, shift in species composition, zones of bottom water hypoxia which is highly detrimental for biological diversity [4,5].  The interplay of nutrients, expressed as the stoichiometric ratio of their supply and subsequent shifts in this ratio during uptake by the biota, has become an important topic in contemporary biogeochemical studies [6]. In many urbanized coastal regions, anthropogenic inputs have altered the composition of nutrient stoichiometry, which may, in turn, exacerbate certain toxic species to proliferate [7]. This is particularly true in the coastal waters of Kerala, southwest coast of India where nutrient availability is strongly influenced from riverine flux, domestic sewage effluents, seasonal upwelling and increasing cultural eutrophication. Though, the coastal waters are heavily impacted by human nutrient inputs, they are mostly understudied. The present study therefore discusses the seasonal and spatial variability in the nutrient distribution, stoichiometry, and phytoplankton biomass in the coastal waters of southwest India.  
Materials and Methods

Geographical and environmental background of the study area

The Kerala coastline extending up to 570 km in length consists of beaches, ridges, riverine deposits, backwaters and coastline. The coastal land is characterized by farmlands, coconut plantations and extensive network of backwaters inter- connected with rivers and canals in the landside with most of them open into the coastal region.
Winds in this region are stronger (8- 10 m/s) north easterlies during post monsoon (October � January) and pre monsoon (February � May), while south westerly during monsoon (June � September). The current direction is from south to north during November � January, and it reverses in February with strong north to south currents from May to October [8].
 The coastal towns and villages generate about 351 MLD of untreated sewage and it is disposed in the backwaters which ultimately impinge into the coastal environment. An estimated 17,104 m3/ day of treated effluents from the industries are also discharged into the coastal waters.


 Sampling and Analytical methods
For the present study five different transects from central (Kochi, Chettuva) and northern (Ponnani, Calicut and Kasargod) Kerala coastal waters of southwest India were selected (Figure 1).  Seasonal sampling representing post monsoon, pre monsoon and monsoon were carried out onboard CRV Sagar Purvi/Paschimi during the year 2008. Surface water samples from a distance of 0.5, 1.0, 3.0, 5.0, 7.5 & 10.0 km from the shoreline were taken for chlorophyll a (Chlorophyll a) and nutrient analysis using PVC Niskin Sampler (5L). The samples were filtered on board (Whatmann GF/C (0.45 �m), stored in polyethylene bottles under freezing conditions for subsequent nutrient analysis. Hydrographical parameters such as salinity (psu) and temperature (0C) were measured in situ using standard probes. pH was recorded using a portable pH meter WTW Multi Line P4, having a pH range of 0 � 14, possessing resolution of 0.01 and an accuracy of + 0.05 pH. The chemical estimation of dissolved oxygen was done onboard by Winkler�s method. BOD5 was determined after 5 days of incubation at 20oC on board as well as at the shore laboratory. Nitrate-N (NO3-N), Nitrite-N (NO2-N), Ammonium (NH4-N), Inorganic Phosphate (PO4-P), Inorganic silicate (Si(OH)4-Si) in filtered samples and Total Nitrogen (TN), Total Phosphorus (TP) in unfiltered samples were analysed spectrophotometrically by standard methods [9]. The data quality was ensured through careful standardization, procedural blank measurements, spike and duplicate samples. For Chlorophyll a determination water samples are filtered through glass fiber filter (GF/C; Whatman) with a gentle vacuum (of less than 100 mm Hg). The actual sample volume can range from 100 mL to 4 L, as long as the filter is distinctively green. The sample is then wrapped in aluminum foil and frozen for later analysis. The filter is extracted in 90% acetone, centrifuged, refrigerated in dark for about 20 � 24 hrs and the light absorbance at particular wavelengths (750, 664, 647 and 630 nm) is recorded in a spectrophotometer [10]. Dissolved Inorganic Nitrogen [(DIN) = (NO3-N + NH4-N+ NO2-N)] and PO4 -P, Si(OH)4-Si concentrations were used to calculate atomic ratios of N: P, Si:P and Si:N.
Phytoplankton samples were collected by filtering 1l of surface water through a 50�m sieve. The filtrate was preserved in plastic bottles using 4% formaldehyde. The abundance of phytoplankton was determined by counting with 1 ml concentrated samples using a Sedgewick Rafter chamber at a magnification of 400 X under a phase contrast microscope (Olympus CX41). Major phytoplankton group was identified up to genus level and expressed as % [11]. Primary production was estimated by the light and dark bottle technique following Strickland and Parsons [12].
Statistical analyses 

Principal component analysis (PCA) is one of the best statistical tools for extracting linear relationships among a set of variables [13]. This can be a valuable tool for resource managers for it can provide information regarding the driving environmental variables effect on ecologic response variables [14]. The coastal water quality data were processed by applying PCA. The PCA was carried out with factors having eigen vectors greater than one (Kaiser criterion). Correlation matrix was used in PCA. The principal components were extracted in decreasing order of importance so that the first PC accounts for as much of the variation as possible and each successive component accounts are lesser. The most significant variables in the components represented by high loadings (> 0.6) are taken into consideration for evaluating the components [15].  During PCA the loadings were suppressed to less than 0.1 in absolute value and thus small values are replaced with blanks. The quality of data for factor analysis is confirmed with Kaiser-Meyer-Olkin (KMO) test. The Principal Component loading of water quality variables obtained for each seasons were combined and analyzed. Pearson correlation was also performed to find out the significant relation between hydrographic - nutrient variables and towards the phytoplankton biomass. Multivariate statistical approaches such as PCA and Regression Analysis (Pearson correlation) have been used by researchers for deriving the significance of specific parameters among the data generated [8, 16]. The statistical package, SPSS 11.0 was employed for doing the PCA and Regression analysis.
Results and Discussion

 Hydrographic Characteristics

Temperature of the surface water followed seasonal changes in atmospheric temperature at different regions of the present study (Figure 2a).  An increase in water temperature during pre monsoon and decrease in monsoon season was observed, except at Kasargod transect. The average surface water temperature of coastal stations varied between 28.20 - 29.60, 28.7 - 29.7 and 27.60 - 28.50 �%C during post monsoon, pre monsoon and monsoon respectively. A slight increase in surface water temperature was observed moving towards northward coast.
pH is an important hydrochemical feature indicating the level of dissolved carbon dioxide in water  which in turn can reflect phytoplankton  activity and  DO level in the sea [17]. The pH distribution exhibited significant seasonal and spatial variation (Figure 2b). Spatially pH followed seasonal fluctuations between high in pre monsoon and low in monsoon at all stations. The average surface values ranged from 7.83 -8.07, 8.04 - 8.20, 7.79 - 7.96 during post monsoon, pre monsoon and monsoon respectively. The slightly lower pH recorded in the monsoon  may be due to the biochemical decomposition of organic matter brought to these shallow coastal waters by monsoonal flushing of land  runoff, fresh water mixing brought by rivers and increased precipitation. 
Salinity plays an important role in sustaining aquatic life. Average surface salinity fluctuated seasonally, between 30.87 � 31.72, 30.85 -32.77, 27.48 � 30.12 during post monsoon, pre monsoon and monsoon respectively at all stations (Figure 2c). The generally high values of salinity noted in the study region during pre monsoon may be due to less influx of river water and increased evaporation during this period whereas the lower salinity of monsoon period is due to the heavy influx of river runoff and precipitation, when compared to other seasons.
Dissolved oxygen values of surface waters exhibited significant spatial and seasonal variations. An average concentration for surface water varied between 4.56 � 5.23, 5.53 � 5.93, 3.62 � 5.62 mg O2 l-1 during post monsoon, pre monsoon and monsoon respectively (Figure 2d). In general, the distribution of DO indicated high average values in surface and the presence of well oxygenated waters even though there were slight fluctuations at certain stations especially at Calicut and Kasargod region during monsoon and at Kochi during pre monsoon. At Kochi  the average concentration during pre monsoon was 3.43 mg O2 l-1. The amount of oxygen dissolved is governed by a number of factors such as temperature, organic matter degradation, primary productivity, respiration etc. DO maximum in the surface layer especially during the pre monsoon period (February�May) was reported earlier [18,19]. The intensity of incident solar radiation is very high during this period, which causes the maximum primary productivity to occur a few meters below the sea surface together with the high vertical stability, which result in the observed oxygen maximum. With the exception of Kochi transect all other transect exhibited maximum DO. Low DO noticed at Kochi stations may be due to the excessive phytoplankton production which should have augmented the concentration of organic matter in the water column thereby consuming the oxygen for its degradation. During the monsoon season low DO values was reflected in the coastal waters at Calicut and Kasargod this can be due to the upwelling phenomenon. This region along the southwest coast of India is one of the major upwelling systems of the world [20]. It was established that upwelling takes place along this coast during monsoon (May to September) thus ensuing productivity [21]. 
The average magnitude of BOD values in the study area was less than 3.0 mg l-1 in most of the stations during all seasons (Figure 2e). Waters with BOD less than 3.0 mg l-1 are known to have received no significant pollution discharges [22]. Albeit, these transects receives large influx of domestic effluents, it was not reflected in its BOD values. A plausible explanation for such low BOD values can be due to the strong dispersive effect of coastal water; the degradable organic matter may get diluted.
Nutrient stoichiometry

Dissolved inorganic nitrogen concentrations didn�t show much spatial variation, although seasonal variation was observed with increased concentration during monsoon at all transect except Kochi region which showed an increase in post monsoon. The concentration of DIN was quiet low; this is evident from the average values of NH4-N, which ranged from 0.16� 0.30, 0.13- 0.38, 0.16 � 0.50 �mol l-1 during post monsoon, pre monsoon and monsoon respectively (Figure 3a). The NO2-N concentrations were always less than 0.5 �mol l-1, it fluctuated from 0.05 � 0.42, 0.06 � 0.16, 0.07 � 0.18 �mol l-1 (Figure 3b); and NO3-N concentrations showed a variation of 0.89 � 6.55, 0.90 � 1.89, 2.20 � 10.80 �mol l-1during post monsoon, pre monsoon and monsoon respectively (Figure 3c). Based on the average values, the concentrations of dissolved inorganic nitrogen forms followed the order NO3-N >NH4-N > NO2-N. The combined inorganic nitrogen which is added to the coastal waters by terrestrial drainage and river water systems contain substantially greater amounts of combined nitrogen than that occur in open sea water. Biological processes result in interconversion of various forms of nitrogen.  NO3�N is the dominant form of combined inorganic nitrogen in well-oxygenated waters thus dominates among the nitrogen forms [23]. The levels of TN displayed marked variations and its concentration in surface water varied from 10.93 � 18.20, 8.62 -15.37, 11.34 -27.74 �mol l-1 during post monsoon, pre monsoon and monsoon respectively (Figure 3d). Based on the mean values during each season, DIN accounted for less than 20% of TN in surface waters at all transects. However, exception were noticed at Kochi which accounted for nearly 40.70 % during post monsoon, 49.20% at Ponnani during pre monsoon, 22.03%  and 63.46% at Kasargod during pre monsoon and monsoon respectively (Figure 3e). The large difference between TN and DIN concentrations suggest that nitrogen is found in the coastal waters mostly in organic forms. This result is in agreement with the general view of microbial food web and phytoplankton dynamics, in which NH4-N, NO2-N and NO3-N are rapidly processed by phytoplankton and other microbial components. Meanwhile, the organic nitrogen is assimilated by aquatic organisms in a slower rate [24]. In the eutrophic Bay of Koper (North Adriatic), the relative composition of total nitrogen comprised of 11.3% for particulate, 68.8% for dissolved organic and 20.1% for the inorganic forms [25]. DIN levels obtained during this study are remarkably similar than those mentioned above, and suggest limited effect of land based sources on the coastal waters. As per the above observations a limited effect of land based sources on the coastal water cannot be established as pollution problems following the release of untreated domestic wastes, urban drainage and agricultural effluents are well documented in the investigated area. It is possible that denitrifying bacteria are present in these shallow environments utilizing the nitrates for their energy requirement and progressively reduced to gaseous nitrogen. Recent studies suggested that coastal system of the Arabian Sea(west coast of India) have undergone an ecological change due to enhanced nutrient loading from land in which low concentration of nitrite indicates net production of N2O by denitrifiers [26]. This study endorses with the above findings, as the concentration of nitrite was noted low in the present area of investigation which comes under coastal system of the Arabian Sea. On tracing the distributional characteristics of dissolved reactive phosphate the surface concentration varied from 0.85 � 1.65, 0.44 � 1.11, 0.43 � 1.31 �mol l-1 during post monsoon, pre monsoon and monsoon respectively (Figure 3f). The concentration was higher during post monsoon and lower in monsoon season except at Kasargod. The concentrations of dissolved phosphate reported in this study more or less coincide with those of the earlier studies conducted by several workers [ 19, 27, 28] in the nearby regions of the Arabian Sea. In all transects PO4-P concentrations were high in surface waters when compared to dissolved inorganic nitrogen forms, consequently N: P ratios were low, reaching an average of less than 10 at most of transects. This tends to suggest nitrogen is the limiting nutrient for phytoplankton growth in these coastal waters. High N:P ratios was spotted at Ponnani and Calicut during the monsoon season  suggesting  that phosphate could be the limiting nutrient for phytoplankton growth during this season at this transect. Studies have shown that PO4-P can also be a limiting nutrient in coastal areas associated with periods of high river runoff with high N: P loading ratios [29]. Low PO4-P contents could also be related mostly to their sorption and deposition upon to the suspended particles conveyed to the coastal waters from the surrounding mainland by monsoonal flushing. Suzumura et al. [30] reported the effect of composition and physicochemical characteristics of natural particles on phosphate adsorption-desorption processes under various aquatic environment. Mamdouh [31] pointed out that, generally, the typical concentrations of PO4-P for eutrophic coastal waters are above 0.15 �mol l-1 and for highly eutrophic system will be beyond 0.30 �mol l-1. Further, the theoretical half saturation constant (Ks) for uptake of PO4 � P is 0.2 �mol l-1 [32]. In this study, results imply that the high PO4 � P concentrations reflected that there were large excess of PO4 � P, most likely from recycling of P-rich marine sediments. The monsoon rainfall enhance river run off with high N: P loading ratios combined with the sorption of phosphorus by suspended particles, thus removing it to the sediments is causing PO4 � P limitation in the coastal waters at Ponnani and Calicut during monsoon. The spatial and temporal distribution pattern of TP displayed a large variability during the investigation period. In surface water it varied from 0.71 � 2.18, 1.50 -2.25, 0.62 -1.48 �mol l-1 during post monsoon, pre monsoon and monsoon respectively (Figure 3g). Based on the seasonal values, PO4 � P constituted > 30 % of TP, implying that phosphate, in the coastal waters principally accounted by inorganic forms (Figure 3h). The contribution of inorganic phosphorus percentage towards TP reveals short pulses of high and low phosphorus among different seasons. This raises the possibility of organic phosphorus being decomposed into inorganic forms at deeper layers where the water remains stagnant which gradually moves up to the surface. These data also suggested that the coastal waters are moderately polluted. Such conclusion is consistent with indications provided by Nalewajko and Lean [33] who pointed out that in moderately polluted coastal waters, the relative importance of phosphorus forms is: 28.5� 98% for particulate, 1.2 � 4% for colloidal, 0.1� 22% for reactive phosphate and 0.1� 6% for dissolved organic P. The respective levels of TP and TN in oligotrophic waters are 0.27 and 47.2 �mol l-1, whereas in mesotrophic waters it reaches 0.89 and 53.8  �mol l-1 and in eutrophic seawaters its value are 2.81 and 133.9 �mol l-1 respectively [31]. These levels when compared with those reported in this study indicate that southwest coastal waters of India are within the mesotrophic to eutrophic conditions in terms of TP. Considering TN it falls under oligotrophic waters. This is caused due to increased denitrification happening in the coastal waters which is discussed earlier. 
The distribution pattern of SiO4-Si concentrations displayed only small spatial and seasonal variations. The seasonal range was found to follow the order monsoon > post monsoon > pre monsoon. The study revealed the surface concentration of SiO4-Si in the range 7.19 � 9.80, 4.25 � 7.63, and 9.26 � 14.06 �mol l-1 during post monsoon, pre monsoon and monsoon respectively (Figure 3i). Seasonal variation indicated higher concentration during monsoon due to increased precipitation, land drainage and river discharge from the SW monsoon and lowest in pre monsoon where the river discharge is at its lowest. The supply of dissolved silica from land usually makes large diatoms generally the most dominant phytoplankton group. This results in shorter food chains, with only three trophic levels in the upwelling zones compared to up to six trophic levels in the oligotrophic open ocean [34].
Plots of the atomic Si:P against N:P ratios in the surface waters of southwest coast  revealed nitrogen as the nutrient which is potentially limiting for phytoplankton biomass growth (Figure 4). The data points in the left quadrant (N:P < 16:1) are indicative of N limitation, in the right quadrant are indicative of P limitation and of Si limitation in the lower left quadrant. In the present study the quadrant with the most data points is the left quadrant, which indicates more frequent occurrences of potential limitation of a nitrogen nutrient. A decrease in Si: N ratio below 1 leads to a functional group shift from diatoms to coccolithophores and flagellates (causing HABs) which could potentially affect for food web structure, and affecting fisheries and biogeochemical fluxes [35]. The near shore coastal region of the investigated area has not reported any incidence of harmful algal blooms in spite of increased domestic discharges. A plausible reason can be the consistency of Si: N ratio maintaining the value greater than unity for all season. In this study, phytoplankton samples examined above 50 �m centric size, diatoms were the most abundant group contributing to the phytoplankton biomass (Figure 5). The species distribution chart(only major contributing species are represented) indicates Chaetoceros, contributing to > 20 % of the phytoplankton population in post monsoon and monsoon at each transect, except at Ponnani where the community structure was dominated by Skeletonema (> 25%). The seasonal shift in population was explicit in pre monsoon, where Skeletonema contributing > 22% at Kochi and Ponnani, Asterionella ( >23%) at Chettuva and Leptocylindrus (19%) at Calicut and Kasargod. Arrigo [36] have characterized the dominance of different algal groups based on stoichiometric ratio. If N: P ratios exceed 30 then proliferation of dinoflagellates will take place and if it descends to 10 then plankton domination will be mainly of diatoms. This characterization corroborates the stoichiometric ratios established in this study.
 Biological Characteristics.
The mean concentration of Chlorophyll a in surface waters varied from 7.11 � 19.62, 7.45 � 18.08, 10.12 � 22.07 mg m-3 and primary productivity from 10.94 � 24.25, 14.66 � 16.28, 10.57 -14.11 mgC m-3 hr-1 during post monsoon, pre monsoon and monsoon respectively (Figure 6a, b). High concentrations of Chlorophyll a ranging from 18.08 mg m-3  to 22.07 mg m-3 were observed at Kochi during the study period. Primary productivity in the region was found to be in the range of mgC m-3 hr-1. In general, biological productivity of a region is determined by three factors such as light, nutrients and primary production. At Kochi the increase in plant pigment is largely due to river runoff and also drainage rich in nutrient content from the urban agglomerations, thus enhanced productivity. Balachandran et al. [37] has pointed out the role of photosynthetic pigments as indices of biological productivity along the southwest coast of India. The maximum production of chlorophyll a along southwest coast was found to take place during monsoon due to upwelling after which there is a decline in its production. Primary productivity was found higher during post monsoon season at all transect, perhaps high light penetration and less suspended solids may be playing a vital part. Imeri et al. [38] in the evaluation of trophic state of a lagoon stated that the levels of Chlorophyll a in the oligotrophic waters are < 2.5 mg m-3, whereas in mesotrophic waters reach between 2.5 � 8.0 mg m-3 and in eutrophic seawaters 8.0 � 25 mg m-3. The foregoing trophic state evaluation when compared with those in this study showed that the waters are within eutrophic conditions (8.0 � 25 mg m-3) in terms of Chlorophyll a concentration, which signifies high biological productivity. Most plankton variability appears to be driven by diatom blooms (Fig. 5), its growth and bloom formation is commonly controlled by both N and Si input in the coastal environment, and other factors such as light availability, mixing depth and water temperature can play interactive controlling roles. Diatoms are important for several reasons that with their mineralized siliceous structure they sink faster; their cells being large they support growth of larger zooplankton (produce fast sinking pellets). All these process can enhance the biological pump in which the production of carbon in surface water is exported to the sediments.
Factor Analysis
The varimax rotated results along with eigen values and percent of variance are summarized in Table 1. The PCA of surface water quality extracted four factors (principal component) with eigen values >1. These composite variables captured 74.80 % of the variation in the original data. Factor 1 explained 42.20% of the total variance and is associated with strong positive loadings of ammonia, silicate, Chlorophyll a; strong negative loading of salinity and pH. In this case ammonia, silicate and Chlorophyll a are correlated significantly with each other, suggesting an increase in the concentration of silicate and ammonia is enhancing the phytoplankton biomass. These variables have significant inverse correlations with salinity and pH establishing the diluting effect of river water, which acts as a local surface source of silicates and terrestrial input such as wastes from agricultural run-off, domestic sewage as the source for ammonia (Table 2). Ammonia is known to be the preferred form of inorganic nitrogen for phytoplankton and silicate for planktons having silicified structures (eg. diatoms) indicating influence of riverine nutrients leading to photosynthesis maxima. Hence, Factor 1 can be termed as the Riverine Factor. The second factor showed 15.90 % of the total variance and is associated with strong positive loadings of phosphate and TP. A significant correlation was observed between the above two variables. This suggests there is increased concentration of phosphate in the coastal waters whose source can be traced to anthropogenic nutrient inputs. Factor 2 can be termed as Phosphorus Factor. The third factor accounts for 8.82 % of the total variance and contains no loading of variables which signifies some processes other than physico-chemical and biological variables affecting the system. It is deciphered, in this case, considering the high abundance of phytoplankton biomass and one of the important factors which exacerbate the production of plankton is upwelling which takes place along this coast during the monsoon. Factor 3 can be termed as Upwelling Factor. Factor 4 accounts for 9.73 % of the total variance and contains independent strong positive loading of Dissolved Oxygen. The DO condition can correctly characterize waste loads, natural factors such as degree of stratification, water temperature and circulation patterns and finally anthropogenic factors (such as nutrient loading) can also contribute to its event. It is presumed that strong seasonal currents, high photosynthetic activity and winds keeping the coastal water well aerated. Factor 4 can be termed as Aeration factor.
Conclusion 
The present findings established that nitrogen is the limiting nutrient for phytoplankton primary productivity in this coastal region. The N: P ratio is much lower since N is limiting, and also due to excess of orthophosphate in the coastal water. The supply of dissolved Si due to fluvial input makes the large diatoms generally the most dominant phytoplankton group in the coastal region. Addition of nutrient load due to anthropogenic influence reinforced by seasonal upwelling has made the coast a biologically productive zone. Both anthropogenic and natural forcing reasonably by riverine, phosphorus, upwelling and aeration are creating an ecological change in the southwest coastal waters.

ACKNOWLEDGEMENT
The authors thank Dr N P Kurian, Director, CESS for the facilities provided. The financial assistance from Ministry of Earth Science, New Delhi in the form of a sponsored project Coastal Ocean Monitoring and Prediction System (COMAPS) is gratefully acknowledged. We are also thankful to crew members of Costal Research Vessels Sagar Purvi/Paschimi (Ministry of Earth Science, Govt.of India).








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Tables


Table 1. Varimax factor analysis using PCA and identified principal components of the surface coastal waters along the southwest coast of India.
Table 2. Correlation matrix among the hydrographic � nutrient � biological parameters of the surface coastal waters along the southwest coast of India




Figures

Figure 1. Area of Investigation along the southwest coast of India.
Figure 2.  Seasonal variability of hydrographic parameters of the surface coastal water at sampling transects along the southwest coast of India shown through box-whisker plot.

Figure 3.  Seasonal variability of nutrients of the surface coastal water at sampling transects along the southwest coast of India shown through box-whisker plot.

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Figure 5. Phytoplankton variability in the surface coastal water along the southwest coast of India.
Figure 6.  Seasonal variability of biological characteristics of the surface coastal water at sampling transects along the southwest coast of India shown through box-whisker plot.










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